Towards artificial intelligence at scale in the chemical industry. Issue 6 (25th February 2022)

• Record Type: Journal Article
• Authors: Chiang, Leo H.; Braun, Birgit; Wang, Zhenyu; Castillo, Ivan
• Is Part Of: AIChE journal. Volume 68:Issue 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-25
• Subjects: artificial intelligence -- fault diagnosis -- industrial applications -- machine learning -- optimization; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.17644
• Languages: English
• ISSNs: 0001-1541

Abstract

Abstract: In the Industry 4.0 era, the chemical industry is embracing broad adoption of artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic view of how the industry is transforming digitally towards AI at scale. First, a historical perspective on how the industry used AI to aid humans in better decision‐making is shown. Then state‐of‐the‐art AI research addressing industrial needs on reliability and safety, process optimization, supply chain, material discovery, and reaction engineering is highlighted. Finally, a vision of the plant of the future is illustrated with critical components of AI‐ready culture, model life cycle management, and renewed role of humans in chemical manufacturing.